180 citations
- Massachusetts Institute of TechnologyUS38 papers
- University of BonnDE37 papers
- University of OxfordGB36 papers
- Centre National de la Recherche ScientifiqueFR35 papers
- Centro Brasileiro de Pesquisas FísicasBR35 papers
- École Polytechnique Fédérale de LausanneCH35 papers
- Lamarr Institute for Machine Learning and Artificial Intelligence35 papers
- Ruhr University BochumDE35 papers
- Sorbonne UniversitéFR35 papers
- University of BolognaIT35 papers
- University of CambridgeGB35 papers
- University of SienaIT35 papers
5 papers · 1 filter
Improving the Generalization of Adversarial Training with Domain Adaptation
Chuanbiao Song, Kun He, Liwei Wang +1
By injecting adversarial examples into training data, adversarial training is promising for improving the robustness of deep learning models. However, most existing adversarial tra…
Time-Agnostic Prediction: Predicting Predictable Video Frames
Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros +1
Prediction is arguably one of the most basic functions of an intelligent system. In general, the problem of predicting events in the future or between two waypoints is exceedingly…
AGIL: Learning Attention from Human for Visuomotor Tasks
Ruohan Zhang, Zhuode Liu, Luxin Zhang +4
When intelligent agents learn visuomotor behaviors from human demonstrations, they may benefit from knowing where the human is allocating visual attention, which can be inferred fr…
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
Kurtland Chua, Roberto Calandra, Rowan McAllister +1
Model-based reinforcement learning (RL) algorithms can attain excellent sample efficiency, but often lag behind the best model-free algorithms in terms of asymptotic performance. T…
Recent Advances in Neural Program Synthesis
Neel Kant
In recent years, deep learning has made tremendous progress in a number of fields that were previously out of reach for artificial intelligence. The successes in these problems has…